The FDA\u2019s GalaxyTrakr uses AI to speed troubleshooting, allowing scientists to focus on identifying contaminated food before outbreaks spread.<\/p>\n
As food safety systems continue to grow more complex, AI-assisted investigation paired with human oversight is helping to ensure the FDA\u2019s GalaxyTrakr remains available when outbreaks demand the fastest possible response.\u00a0<\/p>\n
The GalaxyTrakr platform sits at the center of that effort, allowing microbiologists to analyze DNA fingerprints from pathogens found in food samples and determine whether they are linked to outbreaks. The platform helps scientists identify clusters of bacteria, compare them against previous cases and quickly determine whether contaminated food should be pulled from the market.\u00a0<\/p>\n
\u201cWe need to be able to make those decisions quickly. This data is very actionable,\u201d said Errol Strain, senior information biologist at the FDA, at the AWS Summit in Washington, D.C. Tuesday. \u201cIf we identify a contaminated product that\u2019s making somebody sick, we want to get it off the market as quickly as we can.\u201d\u00a0<\/p>\n
GalaxyTrakr is the FDA\u2019s version of the public Galaxy bioinformatics analysis platform, customized with workflows designed specifically for foodborne pathogens. According to Strain, FDA laboratories process roughly 40 to 60 bacterial isolates each week while simultaneously tracking five to 10 active foodborne outbreaks. <\/p>\n
\u201cGalaxy lets us put wrappers and interfaces in containerized workflows, so that those people who are doing that analysis in the lab can just upload the data, push a button, go back to process some samples in the lab, and get a report out,\u201d Strain said.\u00a0<\/p>\n
But when those workflows fail, diagnosing the problem has historically been slow.<\/p>\n
Because GalaxyTrakr relies heavily on open-source software and bioinformatics tools, failures can originate almost anywhere, such as improperly uploaded data, user mistakes, software bugs, infrastructure problems and storage limitations. Troubleshooting workflows that might involve 10 to 15 steps often require engineers to manually sift through logs spread across multiple AWS services and Galaxy components.\u00a0<\/p>\n
\u201cWe can\u2019t take days to solve that problem,\u201d Strain said. \u201cWe really need hours to get the system back up to triage the data.\u201d\u00a0<\/p>\n
Jimmy Sanders, one of the lead architects for deploying GalaxyTrakr, said the platform has grown dramatically since its deployment in 2017. What began with fewer than 20 users now supports more than 500 active users who collectively submit about 80,000 jobs through an architecture spanning roughly 10 AWS services. <\/p>\n
But that growth came with additional challenges, Sanders said. \u00a0<\/p>\n
\u201cMany times we\u2019d have some active incident, and it would take days, if not almost a week sometimes, to really hone in on a particular issue,\u201d he said. <\/p>\n